The present invention relates to rescaling data. More specifically, the present invention relates to filtering data to allow more rate reduction. Still more specifically, the present invention provides techniques for filtering transform coefficients associated with an input data sequence (e.g. an audio segment or a video image) to provide modified transform coefficients associated with a modified output data sequence.
Video data is one particularly relevant form of data that can benefit from improved techniques for changing the associated bandwidth requirements. Video rescaling schemes allow digitized video frames to be represented digitally in an efficient manner. Rescaling digital video makes it practical to transmit the compressed signal by digital channels at a fraction of the bandwidth required to transmit the original signal without compression. Generally, compressing data or further compressing compressed data is referred to herein as rescaling data. International standards have been created on video compression schemes. The standards include MPEG-1, MPEG-2, MPEG-4, H.261, H.262, H.263, H.263+, etc. The standardized compression schemes mostly rely on several key algorithm schemes: motion compensated transform coding (for example, DCT transforms or wavelet/sub-band transforms), quantization of the transform coefficients, and variable length coding (VLC).
The motion compensated encoding removes the temporally redundant information inherent in video sequences. The transform coding enables orthogonal spatial frequency representation of spatial domain video signals. Quantization of the transformed coefficients reduces the number of levels required to represent a given digitized video sample and reduces bit usage in the compression output stream. The other factor contributing to rescaling is variable length coding (VLC) that represents frequently used symbols using code words. In general, the number of bits used to represent a given image determines the quality of the decoded picture. The more bits used to represent a given image, the better the image quality. The system that is used to compress digitized video sequence using the above described schemes is called an encoder or encoding system.
More specifically, motion compensation performs differential encoding of frames. Certain frames, such as I-frames in MPEG-2, continue to store the entire image, and are independent of other frames. Intracoded frames, such as B-frames or P-frames in MPEG-2, store motion vectors associated with the movement of particular objects in the frames. The pixel-wise difference between objects is called the error term, which can be stored in P and B frames. In MPEG-2, P-frames reference a single frame while B-frames reference two different frames. Although this allows fairly high reduction ratios, motion compensation is limited when significant changes occur between frames. When significant changes occur between frames in a video sequence, a large number of frames are encoded as reference frames. That is, entire images and not just motion vectors are maintained in a large number of frames. This precludes high reduction ratios. Furthermore, motion compensation can be computationally expensive.
Each frame can be converted to luminance and chrominance components. As will be appreciated by one of skill in the art, the human eye is more sensitive to the luminance than to the chrominance of an image. In MPEG-2, luminance and chrominance frames are divided into 8×8 pixel blocks. The 8×8 pixel blocks are transformed using a discrete cosine transform (DCT) and scanned to create a DCT coefficient vector. Quantization involves dividing the DCT coefficients by a scaling factor. The divided coefficients can be rounded to the nearest integer. After quantization, some of the quantized elements become zero. The many levels represented by the transform coefficients are reduced to a smaller number of levels after quantization. With fewer levels represented, more sequences of numbers are similar. For example, the sequence 4.9 4.1 2.2 1.9 after division by two and rounding becomes 2 2 1 1. As will be described below, a sequence with more similar numbers can more easily be encoded using VLC. However, quantization is an irreversible process and hence introduces loss of information associated with the original frame or image.
VLC encoding takes the most common long sequences of numbers of bits and replaces them with a shorter sequence of numbers or bits. Data containing fewer common sequences take more bits to encode.
Currently available compression techniques for resealing data (e.g. video or audio) are limited in their ability to effectively compress data sequences for transmission across networks or storage on computer readable media. The available techniques also have significant limitations with respect loss, computational expense, and delay. Various techniques for reducing the bit rate of compressed data sequences including audio and video streams are being developed. Some of the more promising approaches are described in U.S. Pat. No. 6,181,711 titled System And Method For Transporting A Compressed Video And Data Bitstream Over A Communication Channel. Other approaches are described in U.S. patent application Ser. No. 09/608,128 Methods And Apparatus For Bandwidth Scalable Transmission Of Compressed Video Data Through Resolution Conversion and U.S. patent application Ser. No. 09/766,020 titled Methods For Efficient Bandwidth and U.S. patent application Ser. No. 08/985,377 titled System And Method For Spatial Temporal-Filtering For Improving Compressed Digital Video Scaling Of Compressed Video Data. Each of these references is assigned to the assignee of this invention and is incorporated herein by reference for all purposes. It is still desirable to provide additional techniques for rescaling data that improve upon the limitations of the prior art.